Core Insights - AI is not eliminating human work but redistributing human judgment to areas with high ambiguity and significant stakes [1][3] - The main issue in AI adoption is not capability but trust in AI outputs [2][3] Trust Gap - The trust gap is defined as the difference between AI performance and human reliance on its output, which influences where AI can replace or augment human work [3][4] - Two primary factors affecting the trust gap are ambiguity and stakes [3][4] Ambiguity and Stakes - Ambiguity refers to the level of interpretation and judgment required for a task, while stakes refer to the consequences of errors, including financial, legal, reputational, or ethical implications [4][5] - Tasks with low ambiguity and low stakes are rapidly becoming automated, while high ambiguity and high stakes tasks require human involvement [4][5][6] Task Classification - Low ambiguity, low stakes tasks such as basic classification and routine routing are being fully automated [5] - Low ambiguity but high stakes tasks, like compliance checks, are automated but require human oversight [6] - High ambiguity, low stakes tasks utilize AI as an assistant with minimal human oversight [6] - The most critical area is high ambiguity and high stakes tasks, where trust is difficult to establish, such as fraud detection and safety-critical moderation [7]